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Research Article AKNA Is a Potential Prognostic Biomarker in Gastric Cancer and Function As a Tumor Suppressor by Modulating EMT-Related Pathways

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Research Article AKNA Is a Potential Prognostic Biomarker in Gastric Cancer and Function As a Tumor Suppressor by Modulating EMT-Related Pathways Hindawi BioMed Research International Volume 2020, Article ID 6726759, 10 pages https://doi.org/10.1155/2020/6726759 Research Article AKNA Is a Potential Prognostic Biomarker in Gastric Cancer and Function as a Tumor Suppressor by Modulating EMT-Related Pathways Gang Wang , Dan Sun, Wenhui Li, and Yan Xin Laboratory of Gastrointestinal Onco-Pathology, Cancer Institute, The First Affiliated Hospital of China Medical University, Shenyang 110001, Liaoning Province, China Correspondence should be addressed to Yan Xin; [email protected] Received 20 January 2020; Revised 11 March 2020; Accepted 16 April 2020; Published 13 May 2020 Academic Editor: Nicola Cirillo Copyright © 2020 Gang Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The AT-hook transcription factor, AKNA, is a nuclear protein that affects a few physiological and pathological processes including cancer. Here, we investigated the role of AKNA in gastric cancer (GC). By using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot assays, AKNA was found deregulated in both GC cell lines and 32 paired GC tissues. Subsequently, Kaplan-Meier analysis and clinicopathological analysis were conducted using both 32 GC cases’ data above and RNA-Seq data of AKNA in 354 GC patients and the corresponding clinical-pathological data obtained from The Cancer Genome Atlas (TCGA), and AKNA expression was found closely related to location, metastasis, and TNM staging of GC. Then, the potential molecular mechanisms of AKNA in GC were explored by gene set enrichment analysis (GSEA), qRT-PCR, and Western blot assays. AKNA was found to be a hub gene related to homotypic cell to cell adhesion, regulation of cell to cell adhesion, leukocyte cell to cell adhesion, and regulation of T cell proliferation in GC. GO analysis revealed that AKNA involved in the regulation of epithelial- mesenchymal transition (EMT)-related pathways including chemokine signaling pathway, cytokine to cytokine receptor interaction, cell adhesion molecules, and jak-stat signaling pathway in GC. To explore the regulation of AKNA expression, Targetscan and TargetMiner were used to predict the possible miRNA which targeted AKNA and found the expression of AKNA was negatively correlated to miR-762 which could be sponged by circTRNC18. In conclusion, AKNA could function as a tumor suppressor by modulating EMT-related pathways in GC. The expression of AKNA might be regulated by circTRNC18/miR-762 axis. AKNA could serve as a potential biomarker and an effective target for GC diagnosis and therapy. 1. Introduction AKNA, also known as the AT-hook transcription factor, is a nuclear protein with AT-hook motif. Increasing evi- Gastric cancer (GC) is the fifth most frequent malignancies dences indicated crucial function of AKNA might exert in and the third most frequent cause of cancer-related death all multiple cancers. In cervical cancer, single-nucleotide poly- over the world [1]. Despite great advances in the field of diag- morphisms (SNPs) make AKNA a susceptibility genetic fac- nosis and systemic treatment in recent years, the prognosis is tor [5]. AKNA directly binds the A/T-rich promoters unpleasant for GC patients, as the rapid progression to regions of CD40 and CD40 ligand (CD40L) and coordinately advanced stages and the peculiarity of highly metastatic for regulates their expression, thereby activate antitumor GC [2, 3]. In the process of tumor distant metastasis, immune response, while HPV E6, a cervical cancer-related epithelial-mesenchymal transition (EMT) is a vital and initial oncoprotein, could downregulate AKNA and lead to the pro- molecular step [4]. Therefore, an improved understanding gression of cancer [6, 7]. Moreover, by using weighted gene on the underlying mechanisms of the EMT involved in the coexpression network analysis (WGCNA), AKNA was found process of GC metastasis is urgently needed for elucidating to be a hub gene of head and neck squamous cell carcinoma the development of relevant therapeutic approaches. (HNSCC) which is related to the immune response [8]. 2 BioMed Research International Recently, Camargo et al. reported that AKNA could regulate using PrimeScript Master Mix (TaKaRa, Japan) for cDNA EMT in neurogenesis [9]. As is well known that the expression according to the manual instructions. The primers were con- of a certain mRNA could be regulated by circRNA which com- structed and synthesized by Sangon Biotech (Shanghai, petitively sponge corresponding miRNA, circRNAs are a China). The qRT-PCR assay was performed, and the expres- unique category of RNA molecules that were first identified sion levels were calculated using the 2 − △△Ct method. in plant viruses in the 1970s [10]. Recently, they have aroused Sanger sequencing on the circTRNC18 qRT-PCR product extensive attention as various circRNAs were found to play was conducted by Sangon Biotech (Shanghai, China) to vali- different roles in multiple diseases, especially in cancers [11, date the specificity of the divergent primers and to confirm 12]. Growing evidences demonstrate that circRNAs usually the back-splice junction sequence of circTRNC18 was consis- regulate tumor progression and metastasis by affecting EMT tent with that from circBase database. Glyceraldehyde-3- [13]. CircTRNC18, a circRNA alias hsa_circ_0006772, which phosphate dehydrogenase (GAPDH) was used as the internal is transcripted from TNRC18 gene, was reported to negatively reference for circTRNC18 and AKNA expression detection, regulate trophoblast cell migration and EMT via regulating and U6 snRNA was used as the internal reference for miR-762/Grhl2 axis in preeclampsia [14]. By using bioinfor- miR-762 expression detection. The reaction settings of ° matics tools, we predicted that circTRNC18 could serve as a the two-step PCR were as follows: 95 C for 30 s; 40 cycles ° ° ceRNA of AKNA by competing sponge miR-762. However, of 95 C for 5 s, annealing at 55 C for 30 s; dissolving curve ° ° ° the expression and regulatory role of circTRNC18/miR-762/ at 95 C for 15 s, 60 C for 30 s, and 95 C for 15 s. The AKNA axis in GC progression is not yet clear. primers were as follows: circTRNC18: forward: 5′-GGTG The present study was novel in demonstrating that GCAGGGCTTGGAACGG-3′ and reverse: 5′-GCCTTG AKNA, a potential target of miR-762, was deregulated in TCTTGGAGCAGAGCTTC-3′; miR-762: forward: GGGG GC and was closely related to location, metastasis, and CTGGGGCCGGGGC and reverse: universal downstream TNM staging of GC. GSEA analysis revealed AKNA could primer; AKNA: forward: 5′-GCACCAAGTCCGCAGCATC function as a hub gene of GC by regulating EMT-related C-3′ and reverse: 5′-CGCCATCCAGGTCTCCTCCA G-3′; pathways. AKNA might be regulated by circTRNC18/miR- ′ ′ 762 axis in GC. The present study provides a promising GAPDH: forward: 5 -GAGTCAACGGATTTGGTCGT-3 ′ ′ biomarker and a potential target for GC treatment. and reverse: 5 -TTGATTTTGGAGGGATCTCG-3 ; U6: forward: 5′-GGAACGATACAGAGAAGATTAGC-3′ and 2. Materials and Methods reverse: 5′-TGGAACGCTTCACGAATTTGCG-3′. 2.1. Clinical Specimen Collection. There were 32 fresh pri- 2.4. Western Blot. Lysis buffer (Beyotime, China) was used to mary GC and matched normal gastric epithelial tissues lyse GC tissues. The harvested protein concentration was acquired from patients with GC undergoing resection in the quantified by microplate reader using a BCA protein kit First Affiliated Hospital of China Medical University. The (Beyotime, China). The proteins successively underwent elec- samples were immediately collected and placed into RNase- trophoresis, transferred membrane, blocked, and then incu- free Eppendorf tubes after resection and put into liquid nitro- bated with primary antibody overnight using anti-AKNA ° gen for 5 min, then were put in storage at -80 C for further (1 : 500, Proteintech, USA), anti-E-cadherin (1 : 1000, CST, use. All primary tumor cases and matching normal tissues USA), anti-N-cadherin (1 : 1000, CST, USA), anti-vimentin were verified by qualified pathologists. Permission was (1 : 1000, CST, USA), and GAPDH (1 : 1000, Origene Co., obtained from the ethics committee of the First Affiliated Ltd., Beijing, China). After incubating with antimouse sec- Hospital of China Medical University, and informed consent ondary antibody (1 : 10000, Origene Co., Ltd., Beijing, China), was obtained from patients. the blot analysis was conducted by an enhanced chemilumi- nescence system. 2.2. Cell Culture. Five GC cell lines AGS, SGC-7901, BGC-823, MNK-45, HGC-27, and human immortalized normal gastric 2.5. Bioinformatics Analysis. RNA-Seq data of AKNA in 354 epithelial cells GES-1 were provided by Genechem Co., Ltd GC patients and the corresponding clinical-pathological data (Shanghai, China). All the cells were maintained and gener- were obtained from TCGA (https://cancergenome.nih.gov/) ated in RPMI 1640 (Gibco, USA) supplemented with 10% [15]. The survival curve was plotted using the Human ° fetal bovine serum (Hyclone, USA) and cultured at 37 Cin Protein Atlas [16]. The potential molecular mechanisms of 5% CO2 atmosphere. Cells were collected when they reached AKNA in GC were explored by GSEA [17, 18], RNA-seq data the platform stage. of 354 GC patients in TCGA, and collection of annotated gene sets from molecular signatures database v7.0 were used 2.3. RNA Extraction and Real-Time PCR. RNA was extracted to categorize enriched genes of AKNA-low expression group. from GC cells and tissues using miRcute miRNA Kits Targetscan and TargetMiner were used to predict the possible (Tiangen Biotech Co., Ltd, Beijing, China) following the miRNA which targeted AKNA [19, 20]. instructions. Then, 30 μl diethylpyrocarbonate (DEPC)- treated water was used to dissolve the extracted total RNA. 2.6. Statistical Analysis. All statistical analyses were con- The concentration and quality of RNA were determined ducted using SPSS25.0 (IBM, NY, USA). Data were presented using a NanoDrop spectrophotometer (Thermo Scientific, as mean ± standard error of the mean. The χ2 test, Student USA).
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